This study aimed to assess the prevalence of insomnia and excessive daytime sleepiness among Polish female college students, with particular attention to potential differences before and after the announcement of the COVID-19 pandemic. In the academic year 2024/2025, 58.2% of the 1.28 million university students in Poland were women, with the most common fields among female graduates being business, administration and law, health and social care, and social sciences [32]. While our sample does not fully reflect the national distribution across disciplines, the overrepresentation of female students is partly attributable to their greater willingness to participate in anonymous online surveys, a trend observed in similar research.

Sleep disorders are an increasingly significant global health concern, with the number of affected individuals rising each year. Our findings highlight that students, in particular, represent a group at heightened risk for developing such disorders. Insomnia is commonly referred to as the most prevalent sleep problem among students [33]. However, in the existing literature, its rates vary from as high as 61.6% among Ethiopian students [34] to 7.7% among German students [35]. Thus, its prevalence varies depending on the population surveyed, the time of data collection, and the use of different validated tools. Individuals in lower socioeconomic status groups are also thought to be at risk for sleep disturbances and associated health consequences [36]. Both insomnia and excessive sleepiness were more prevalent during the early years of university. This is consistent with previous research; for example, Goweda et al. found that the rates of sleep disorders ranged from 88.6% in the second year to 65% in the sixth year [37]. Studies indicate that stress levels are highest in the first year of university and gradually decrease as students adapt to the workload and their new routines [38]. When examining the field of study, medical students had lower rates of insomnia but higher rates of excessive sleepiness compared to their peers. This finding somewhat contradicts most research, which typically shows that medical students report the highest rates of disrupted sleeping patterns [8,39]. Although sleep quality is a concern across all fields of study, medical students may be particularly vulnerable due to the unique demands of medical education. They face high academic demands, long study and clinical hours, and other factors that can cause sleep disturbances and disorders [6]. In our study, the COVID-19 pandemic announcement did not impact insomnia rates, but it did lower excessive sleepiness. Given the timeline of our data collection, it is important to note that the data were gathered during the lockdown, with most university activities conducted through remote study platforms and outside activity severely limited. Meta-analyses indicate that the pandemic indeed led to changes in sleep patterns [40]. Several studies show an increase in sleep duration, with participants going to bed later, getting out of bed later, and taking more naps during the day [41,42]. However, nearly one in five participants reported a decrease in their sleep duration, and the results varied depending on factors such as their place of residence [40]. This highlights a significant discrepancy in the available data, making it difficult to draw definitive conclusions. Fewer external demands and more flexible daily schedules may have helped students sleep in a way that better matched their personal chronotypes, leading to less daytime sleepiness. However, ongoing stress and a sense of uncertainty may have kept insomnia levels high despite these changes.

Given the study’s focus on female students, it is important to consider gender-specific factors that may influence the prevalence of sleep disorders. Women have been reported to experience sleep disorders more frequently than men [9]. Nowicki et al. found that, among the general population of Poland, the prevalence of self-reported insomnia was 58.9% in women and 41.4% in men [43]. Psychological and hormonal factors can influence this phenomenon. Women are at a higher risk of developing psychiatric disorders such as depression or generalized anxiety disorder, and these conditions have been linked to sleep disturbances [44]. This higher level of heightened emotional responsiveness can be explained by differences in sex steroid hormone levels between sexes after puberty [45]. In women, hormone levels fluctuate with the menstrual cycle, with documented impacts on self-assessed quality and duration of sleep [46,47]. Some studies have reported that high estradiol and progesterone levels are associated with prolonged arousal and wakefulness [48].

Substance use and sleep patterns are bidirectionally linked, influencing each other in significant ways. Participants who used psychostimulants and sedatives were more frequently diagnosed with insomnia. For psychostimulant users, sleep disturbances are often a direct consequence of substance use, as studies have shown that psychostimulant consumption negatively impacts sleep quality [15]. In a study of 498 adolescent participants aged 18 to 25, Pittsburgh Sleep Quality Index (PSQI) global scores were positively and significantly associated with the number of cigarettes smoked per day and the number of days of non-medical prescription stimulant (NPS) use [49]. It is important to note that the relationship between stimulants and sleep is complex, with studies offering conflicting evidence. Additionally, sedative users might have initially turned to these substances to address pre-existing insomnia. While research indicates that non-medical use of prescription sedatives can decrease sleep quality in students [50], it also suggests that sedatives can improve sleep quality in other populations when comparing effects before and after use [51]. In our study, the impact of substances on excessive daytime sleepiness is evident, with every substance showing a significant relationship with its prevalence. This bidirectional relationship suggests that sleep and alertness alterations, while not the primary reinforcing mechanism, may contribute to the initiation and maintenance of drug and alcohol abuse and increase the risk of relapse [52].

The COVID-19 pandemic influenced substance use, which may be connected to changes in the rates of sleep disturbances. The results of this study suggest that students were most likely to consume alcohol both before and during the pandemic. However, they consumed alcohol much less frequently during the initial phase of the pandemic. This aligns with studies suggesting that more Europeans limited their alcohol consumption when the pandemic started [53,54]. As most students consume alcohol in social settings [55], it could explain why isolation affected its intake. It is worth noting that, despite the general trend, some studies found that 14–16% of adults reported an increase in their intake [56]. Another study found that, in the early stages of the pandemic, one in four students surveyed developed riskier alcohol-related behaviors [57]. Sedative use increased after the start of the pandemic, which aligns with findings from most studies [58]. This rise may be attributed to heightened anxiety levels during lockdown [59,60], which can significantly disrupt sleep patterns, leading to issues like insomnia and a greater reliance on medication. Interestingly, some studies also report an increase in health-promoting behaviors, such as higher levels of physical activity, increased consumption of fruits and vegetables, and reduced tobacco use [61]. It is possible that the fear of the virus and death during the COVID-19 pandemic motivated these healthier habits. However, substance use patterns during the pandemic appear to vary based on factors like location, time period, and individual predispositions. Therefore, ongoing monitoring is essential.

We acknowledge several limitations of this study, including the data collection methodology, which involved using an anonymous online questionnaire. While this approach allows for reaching a large audience and increases survey participation rates, it also presents challenges. The data are cross-sectional, capturing a single point in time. Therefore, causal relationships between variables cannot be established. Prior research indicates that anonymous online surveys can significantly reduce respondents’ anxiety and boost the likelihood of participation [62]. However, such surveys do not allow the authors to verify the accuracy of the provided data, determine the response rate, and limit the ability to fully verify participants’ eligibility and prevent duplicate or inauthentic responses. The data collection spanned five years, covering different social, academic, and epidemiological contexts, and the analysis did not specifically address this temporal variation. The psychometric tools used rely on respondents’ subjective assessments and require verification and objectification by a trained medical professional. The survey did not include questions regarding sleep disorders confirmed by a medical specialist, nor did it assess whether participants were undergoing treatment for such conditions. It also did not include questions about prior COVID-19 infection, which is known to potentially affect brain activity and sleep patterns [63]. The study did not include objective diagnostic methods such as polysomnography, which remains the gold standard for the assessment of sleep disorders [64]. The interpretation of this study’s findings is further limited by the lack of data on chronic conditions, chronic medication use, and potential mental health issues within the surveyed population. However, it should be noted that the psychometric tools employed are recognized as valid and effective research instruments. Although the Pittsburgh Sleep Quality Index (PSQI) is a widely used tool for assessing sleep quality, we chose the Athens Insomnia Scale (AIS) and the Epworth Sleepiness Scale (ESS) for this study because they specifically target insomnia symptoms and daytime sleepiness. Both instruments are concise, validated, and well-suited for large-scale online surveys. Due to the exploratory nature and methodological constraints of our study, we focused on univariate and bivariate associations, which do not account for potential confounding. Future research should incorporate multivariate models to better assess independent associations and explore potential effect modification. The absence of multivariate adjustment means the observed associations may be confounded by unmeasured factors such as mental health status, workload, or chronotype.